The use of recombining genetic markers for demographic inference

描述（由申请人提供）：拟议的研究涉及对历史迁移模式的推断。传统的人口迁移遗传模型假设人口在很长一段时间内以恒定的速率交换移民。然而，对于许多物种来说，这种假设可能并不合适。因此，提出了一种计算方法来测试最近移民率的变化并估计相关的人口参数。虽然大多数人口统计学推断方法假设所研究的所有遗传标记都是独立的（无关联的），但这种方法将利用沿重组染色体的连锁模式。通过考虑这种联系信息（特别是推断出具有移民起源的DNA片段的长度），人们可以超越估计两个种群之间发生了多少迁移，并且可以说出这种迁移发生的历史时间。在该项目的第一阶段，将利用现有的模拟程序（ms）和推理方法（structure 2.0），研究不同种群历史对迁移DNA片段长度分布的影响。接下来，将开发上述新的推理方法，在最大似然或贝叶斯框架中使用马尔可夫链蒙特卡罗方法。最后，该方法将应用于现有的人类多态性数据集（SNP和微卫星），以检验自人类群体分化以来人口迁移一直不变的原假设。这种分析将允许估计混合人群的人口统计参数，因此将有助于选择人群进行疾病关联的混合绘图研究。

DESCRIPTION (provided by applicant): The proposed research concerns the inference of historical patterns of migration. Traditional population genetic models of migration assume that populations have been exchanging migrants at a constant rate over long periods of time. For many species, however, this assumption may not be appropriate. Therefore, the development of a computational method to test for recent changes in migration rate and to estimate the relevant demographic parameters is proposed. While most methods of demographic inference assume that all of the genetic markers being studied are independent (unlinked), this approach will take advantage of the patterns of linkage along a recombining chromosome. By considering this linkage information (specifically, the lengths of DNA segments that inferred to have migrant origin), one can go beyond estimating how much migration has occurred between two populations, and say something about when, historically, this migration occurred. During the first phase of this project, the effect of various population histories on the length distribution of migrant DNA segments will be investigated, making use of an existing simulation program (ms) and inference method (structure 2.0). Next, the new inference method described above will be developed, using Markov chain Monte Carlo methodology in a maximum likelihood or Bayesian framework. Finally, this method will be applied to existing human polymorphism data sets (both SNP and microsatellite) in order to test the null hypothesis that migration among human populations has been constant since their divergence. This analysis will permit the estimation of demographic parameters for admixed human populations, and will therefore aid in the selection of populations for admixture mapping studies of disease association. Relevance to public health: The goal of the proposed research is to test for historical changes in the rate of migration between populations, and to estimate quantities such as the time since a migration rate change and the magnitude of such a change. The computational method developed will have a variety of applications, including the estimation of demographic parameters in human populations with a history of recent admixture (ancestry from multiple sources), such as African-American, Hispanic, Central Asian and Northern African populations. That information will be relevant in assessing the utility of such populations for admixture mapping studies, which aim to identify genetic variants associated with complex diseases that occur at different frequencies in different populations.